Biology subjects

Van der Linden, A.

Publications and source records attributed to Van der Linden, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Emergence of social recognition in auditory and integrative circuits during pair bonding

Social relationships profoundly shape the perception of communication signals. In animals that form long-term social bonds, sensory cues such as vocalizations, scent, or physical appearance, and rewarding mating experiences can become associated with a bonded mate. While this natural process has hallmarks of some forms of associative learning, little is known about where or how these experiences shape neural circuits over the course of pair bonding. We used whole-brain BOLD fMRI in female songbirds to explore experience-dependent changes in neural activity in response to male songs. Pair bonding experiences drove changes in activation in response to the partners song within secondary auditory areas as well as two regulatory hubs that receive sensory input and connect to circuits that generate behavioral responses. In contrast, mere exposure to the vocal interactions of a neighboring pair did not result in changes in response to the neighbors song within the same areas, suggesting that pair bonding uniquely impacts auditory responses to familiar songs in select sensory and integrative circuits. Moreover, within the areas that showed increased activation for the partners song over the course of pair bonding, we observed diminished activation in response to the partners song after blocking D1 dopamine receptors, indicating a potential role for dopamine in the expression or maintenance of preference for the partners song. Eavesdropping females had changes in neural activation in response to the familiar song in a different suite of brain regions that were not affected by dopamine manipulation. Our data identify a potential circuit in which concurrent activation of sensory, reward, and regulatory hubs integrates multisensory information from social interactions and leads to the emergence of acoustic preferences and formation of long-lasting social bonds.

neuroscience↗

bioRxiv2025

Mapping brain volume changes in the zQ175DN mouse model of Huntington's disease: a longitudinal MRI study

Huntingtons disease (HD) is a progressive neurodegenerative disease affecting motor and cognitive abilities, as well as exhibiting psychiatric manifestations. Studies in people with HD (PwHD) consistently report atrophy of the caudate and putamen as an early pathological event and is therefore considered an early biomarker. Investigating whether similar phenotypic features are apparent in rodent HD models is important since it could have translational potential in evaluating the efficacy of novel therapeutic strategies. We used high-resolution anatomical images to longitudinally investigate brain morphology in the zQ175DN heterozygous mouse model (HET) and wildtype littermates (WT) at 3, 6, and 10 months of age (M), which reflect different stages of phenotypic progression. We investigated volumetric alterations using semi-automatic segmentations of HD on relevant regions-of-interest (striatum, cerebellum, corpus callosum, cerebral cortex, ventricles, and total brain volume) and whole brain voxel-wise Tensor Based Morphometry (TBM) analysis. The striatum showed the earliest progressive lower absolute volume in HET mice compared to WT, starting from 3M, followed by lower absolute volume of cortex and corpus callosum concomitantly at 6 and 10M. TBM highlighted lower relative local volume in the rostral-medial striatum at all ages, and in cerebral cortex in HET mice at 6 and 10M. A bigger relative local volume in the cerebellum was observed at all ages in HET mice, and in the globus pallidus, substantia nigra, at 6 and 10M. Overall, this study revealed key structural abnormalities that resemble the natural history of PwHD. Hence, analysis of brain structure through MRI in the zQ175DN heterozygous mouse model holds potential for testing disease-modifying treatments expected to slow down or prevent structural degeneration. HighlightsO_LIThe striatum of zQ175DN heterozygous mice shows volume decrease at 3 months compared to WT mice C_LIO_LIWidespread volume reductions are observed from 6 months in zQ175DN heterozygous mice C_LIO_LITensor Based Morphometry highlights vulnerability of the dorsomedial striatum in the zQ175DN heterozygous mouse model C_LI

neuroscience↗

bioRxiv2023

Evolution of aberrant brain-wide spatiotemporal dynamics of resting-state networks in a Huntington's disease mouse model

Distinct resting-state networks (RSNs) are differentially altered in the course of Huntingtons disease (HD). However, these RSN changes are depicted using traditional functional connectivity analyses which ignore the dynamic brain states that constitute these RSNs and their time-dependent relationship. Dynamic states are represented by recurring spatiotemporal patterns of propagating cortical and subcortical brain activity observed in low-frequency BOLD fluctuations, called quasi-periodic patterns (QPPs). In this study, we used resting-state fMRI to investigate QPPs in the zQ175DN mouse model of HD at 3, 6 and 10 months of age. We identified age- and genotype-specific short (3s) QPPs, representative of the lateral cortical network (LCN) and the default mode-like network (DMLN), and a long (10s) QPP, the homolog of the human primary QPP, exhibiting the propagation of activity between the LCN and the DMLN. Hyperactivity was present in the caudate putamen and the somatosensory cortex in zQ175DN mice at 3 and 6 months of age. Moreover, DMLN-wide reduction in activation was observed at all ages, where at 6 and 10 months of age the reduced activity gradually advanced into a breakdown of the LCN-to-DMLN propagation. We then investigated the relationship in the timing of peak activity of six brain regions involved in the long QPPs and found that the retrosplenial cortex, a transmodal region which orchestrates multisensory integration, has a premature peak of BOLD activation in zQ175DN mice at 6 months of age, as compared to age-matched controls. Irrespective of either LCN or DMLN activation, this resulted in an asynchrony of the retrosplenial cortex in the peak timing relationships relative to other regions during the long (10s) QPPs. Finally, the normative, age-dependent, wild-type QPPs were significantly decreased in occurrence in the zQ175DN group at each age, indicating the presence of phenotypically-driven LCN and DMLN states as captured with QPPs. As BOLD-dependent variations result from neurovascular coupling, we assessed mutant huntingtin (mHTT) deposition in astrocytes and pericytes, known components of the neurogliovascular unit. These analyses showed increased cell-type dependent deposition starting at 6 months in the caudate putamen, somatosensory and motor cortex, regions that are prominently involved in HD pathology as seen in humans. Our findings provide meaningful insights into the development and progression of altered functional brain dynamics in this HD model, opening potential new avenues for its application in clinical HD research. SUMMARYHuntingtons disease (HD) is marked by irreversible loss of neuronal function for which currently no availability for disease-modifying treatment exists. Advances in the understanding of disease progression can aid biomarker development, which in turn can accelerate therapeutic discovery. We characterized the progression of altered dynamics of whole-brain network states in the zQ175DN mouse model of HD using a dynamic functional connectivity (FC) approach to resting-state fMRI and identified quasi-periodic patterns (QPPs) of brain activity constituting the most prominent resting-state networks. The occurrence of the normative QPPs, as observed in healthy controls, was reduced in the HD model as the phenotype progressed. This uncovered progressive cessation of synchronous brain activity with phenotypic progression, which is not observed with the conventional static FC approaches. This work opens new avenues in assessing the dynamics of whole brain states, through QPPs, in clinical HD research.

neuroscience↗

bioRxiv2023

Season-dependent processing of innate conspecific vocalizations in the male and female European starling (Sturnus vulgaris)

Avian innate nestling begging calls are similar to human infant cries in the behavioral response they elicit. However, it remains unknown whether the auditory processing of innate begging calls changes in seasonal songbirds from non-breeding to breeding season when hormonal neuromodulation of the auditory forebrain occurs. An fMRI experiment was set up to expose male and female European starlings (Sturnus vulgaris) to recordings of seasonal conspecific nestling begging calls in the breeding and non-breeding season. This response was compared with their response to conspecific warble motifs and artificial pure tones, both proven seasonally invariable at least in the male starlings neural response. Our results demonstrate significant seasonal variation in auditory forebrain responses exclusively elicited by begging calls and not by the applied control stimuli. Right Field L and the Caudomedial Nidopallium (NCM) seemed, irrespective of season or sex, more sensitive in response to begging than to control stimuli. A seasonal differential response specifically to begging calls was found in both sexes in a ventral midsagittal region of NCM. Our findings thereby support the functional fine-tuning of vocal communications between sender and receiver in a breeding context for innate vocalizations and are in line with the bi-parenting behavior in this species.

neuroscience↗

bioRxiv2022

Resting-State fMRI reveals Longitudinal Alterations in Brain Network Connectivity in a Mouse Model of Huntington's Disease

Huntingtons disease is an autosomal, dominantly inherited neurodegenerative disease caused by an expansion of the CAG repeats in exon 1 of the huntingtin gene. Neuronal degeneration and dysfunction that precedes regional atrophy result in the impairment of striatal and cortical circuits that affect the brains large-scale network functionality. However, the evolution of these disease-driven, large-scale connectivity alterations is still poorly understood. Here we used resting-state fMRI to investigate functional connectivity changes in a mouse model of Huntingtons disease in several relevant brain networks and how they are affected at different ages that follow a disease-like phenotypic progression. Towards this, we used the heterozygous (HET) form of the zQ175DN Huntingtons disease mouse model that recapitulates aspects of human disease pathology. Seed- and Region-based analyses were performed at different ages, on 3-, 6-, 10-, and 12-month-old HET and age-matched wild-type mice. Our results demonstrate decreased connectivity starting at 6 months of age, most prominently in regions such as the retrosplenial and cingulate cortices, pertaining to the default mode-like network and auditory and visual cortices, part of the associative cortical network. At 12 months, we observe a shift towards decreased connectivity in regions such as the somatosensory cortices, pertaining to the lateral cortical network, and the caudate putamen, a constituent of the subcortical network. Moreover, we assessed the impact of distinct Huntingtons Disease-like pathology of the zQ175DN HET mice on age-dependent connectivity between different brain regions and networks where we demonstrate that connectivity strength follows a nonlinear, inverted U-shape pattern, a well-known phenomenon of development and normal aging. Conversely, the neuropathologically driven alteration of connectivity, especially in the default mode and associative cortical networks, showed diminished age-dependent evolution of functional connectivity. These findings reveal that in this Huntingtons disease model, altered connectivity starts with cortical network aberrations which precede striatal connectivity changes, which appear only at a later age. Taken together, these results suggest that the age-dependent cortical network dysfunction seen in rodents could represent a relevant pathological process in Huntingtons disease progression.

neuroscience↗

bioRxiv2022

Selective cholinergic stimulation of the medial septum-diagonal band of Broca via DREADDs improves spatial learning in healthy rats

The septohippocampal pathway plays an important role in learning and memory. It projects from the medial septum-vertical limb of the diagonal band of Broca (MSDB) to the hippocampus and provides the latter with its main cholinergic innervation. To assess the importance of cholinergic selectivity and timing of MSDB stimulation in modulating learning and memory, we directly compared the effects of several MSDB stimulation strategies in healthy rats. We evaluated the effects of DREADD-mediated selective cholinergic neuronal MSDB stimulation and nonselective neuronal MSDB stimulation on spatial learning and memory in the appetitive radial arm maze and on resting-state brain networks using resting-state functional MRI. DREADDs were activated with the novel DREADD agonist J60. Selective cholinergic MSDB stimulation during - but not after - radial arm maze training improved spatial learning compared with J60-treated sham rats and had no effect on working memory or reversal learning. J60-treated sham rats had a worse working memory than saline-treated sham rats during the reversal phase of the radial arm maze task, suggesting an adverse effect of chronic use of J60. Nonselective MSDB stimulation during training resulted in a loss of appetite and exclusion from the radial arm maze training. Acute selective cholinergic and nonselective MSDB stimulation induced decreased functional connectivity (FC) in the default mode-like network. In addition, acute nonselective MSDB stimulation resulted in increased intrahippocampal FC, while selective cholinergic MSDB stimulation led to globally increased FC with the nucleus accumbens. While the combined effect of radial arm maze learning and the necessary chronic food restriction with or without chronic MSDB stimulation had no observable effect on resting-state networks, chronic food restriction alone globally increased FC in the brain.

neuroscience↗

bioRxiv2022

Dynamics of brain-fluid circulation are altered in the mature-onset Tet-off APP mouse model of amyloidosis

Alzheimers disease (AD), the most common type of dementia, is an incurable brain disorder characterised by the progressive build-up of toxic amyloid-beta (A{beta}) and tau protein aggregates. AD gradually inflicts cognitive functions of an individual such as memory, thinking, reasoning, and language by degrading synaptic function and the integrity of neuronal networks. It has been recently suggested that the efficacy of different brain-clearance systems like the glymphatic system (GS), involved in the removal of toxic waste and homeostatic balance, plays a key role in the pathology of AD. Moreover, the observed coupling between brain fluid movement and global brain activity implies that an alteration of the neuronal network integrity can impact brain fluid circulation throughout the brain and thereby the efficacy of the GS. Here, we investigated the dynamics of brain fluid circulation in Tet-Off APP (AD) mice, a mature-onset model of amyloidosis in which we have recently shown a deterioration of neuronal network integrity by resting-state fMRI. By utilizing dynamic contrast enhanced-MRI and gadoteric acid (Gd-DOTA) T1 contrast agent injected into the cisterna magna, we demonstrated that brain fluid exchange was significantly altered in 14-month-old AD mice compared to control littermates. More specifically, AD mice showed higher Gd-DOTA accumulation in areas proximal to the injection cite and computational modeling of time courses demonstrated significantly lower inflow time constants relative to the controls. Immunohistochemistry demonstrated abundant amyloid plaque burden in the forebrain of the AD group coinciding with extensive astrogliosis and microgliosis. The neuroinflammatory responses were also found in plaque-devoid regions, potentially impacting brain fluid circulation.

neuroscience↗

bioRxiv2021

An in-vivo digital atlas of the spatially reliable cerebral vasculature in mice

Cerebral vascular abnormalities can have a large impact on brain function and have been frequently detected as a comorbidity in various neuropathologies. The mouse is the most common pre-clinical animal model used to investigate neuropathologies and thus cerebral vascular atlases of this species are indispensable. In particular, an atlas derived from multiple animals and that can address inter-subject variability is still absent. The current study presents a mouse cerebral vascular atlas developed from MR 2D-TOF angiograms acquired from a relatively high number (N=21) of 12 weeks old male C57BL/6 mice. The vascular atlas we present depicts large arteries, veins and sinuses that are more spatially reliable across animals than smaller vessels. The atlas is available for download and contains multiple datasets: i) a cerebral vascular atlas; ii) a digital segmentation of large vessels (arteries and veins); iii) a high resolution T2 anatomical background aligned to the atlas; iv) a skeletonized vascular atlas; and v) a vascular graph model. We suggest that these components provide a very potent analysis tool for mouse fMRI data and that the atlas can be used as a template for multimodal brain imaging studies. To this end, we also demonstrate an explicit application of the atlas for the investigation of vascular influences in resting-state fMRI.

neuroscience↗

bioRxiv2021

Unravelling the role of thyroid hormones in seasonal neuroplasticity in European Starlings (Sturnus vulgaris)

1Thyroid hormones clearly play a role in the seasonal regulation of reproduction, but any role they might play in song behavior and the associated seasonal neuroplasticity in songbirds remains to be elucidated. To pursue this question, we first established seasonal patterns in the expression of thyroid hormone regulating genes in male European starlings employing in situ hybridization methods. Thyroid hormone transporter LAT1 expression in the song nucleus HVC was elevated during the photosensitive phase, pointing towards an active role of thyroid hormones during this window of possible neuroplasticity. In contrast DIO3 expression was high in HVC during the photostimulated phase, limiting the possible effect of thyroid hormones to maintain song stability during the breeding season. Next, we studied the effect of hypothyroidism on song behavior and neuroplasticity using in vivo MRI. Hypothyroidism inhibited the photostimulation-induced increase in testosterone, confirming the role of thyroid hormones in activating the hypothalamic-pituitary-gonadal (HPG) axis. Surprisingly, apart from the myelination of several tracts during the photostimulated phase, most neuroplasticity related to song production was unaffected by hypothyroidism. Remarkably, T3 plasma concentrations were negatively correlated to the microstructural changes in several song control nuclei. Potentially, a global reduction of circulating thyroid hormones during the photosensitive period is necessary to lift the brake imposed by the photorefractory period, whereas local fine-tuning of thyroid hormone concentrations through LAT1 could activate underlying neuroplasticity mechanisms. Given the complexity of thyroid hormone effects, this study is a steppingstone to disentangle the influence of thyroid hormones on seasonal neuroplasticity.

neuroscience↗

bioRxiv2021

A novel imaging ligand as a biomarker for mutant huntingtin-lowering in Huntington's disease

Huntingtons disease (HD) is a dominantly inherited neurodegenerative disorder caused by a CAG trinucleotide expansion in the huntingtin (HTT) gene that encodes the pathologic mutant HTT (mHTT) protein with an expanded polyglutamine (PolyQ) tract. While several therapeutic programs targeting mHTT expression have advanced to clinical evaluation, no method is currently available to visualize mHTT levels in the living brain. Here we demonstrate the development of a positron emission tomography (PET) imaging radioligand with high affinity and selectivity for mHTT aggregates. This small molecule radiolabeled with 11C ([11C]CHDI-180R) enables non-invasive monitoring of mHTT pathology in the brain and can track region-and time-dependent suppression of mHTT in response to therapeutic interventions targeting mHTT expression. We further show that therapeutic agents that lower mHTT in the striatum have a functional restorative effect that can be measured by preservation of striatal imaging markers, enabling a translational path to assess the functional effect of mHTT lowering.

neuroscience↗

bioRxiv2021

The photosensitive phase acts as a sensitive window for seasonal multisensory neuroplasticity in male and female starlings

Traditionally, research unraveling seasonal neuroplasticity in songbirds has focused on the male song control system and testosterone. We longitudinally monitored the song and neuroplasticity in male and female starlings during multiple photoperiods using Diffusion Tensor and Fixel-Based techniques. These exploratory data-driven whole-brain methods resulted in a population-based tractogram uncovering microstructural sexual dimorphisms in the song control system and beyond. Male brains showed microstructural hemispheric asymmetries, whereas females had higher interhemispheric connectivity, which could not be attributed to brain size differences. Only females with large brains sing but differ from males in their song behavior by showing involvement of the hippocampus. Both sexes experienced multisensory neuroplasticity in the song control, auditory and visual system, and the cerebellum, mainly during the photosensitive period. This period with low gonadal hormones might represent a sensitive window during which different sensory and motor systems in telencephalon and cerebellum can be seasonally re-shaped in both sexes.

animal behavior and cognition↗

bioRxiv2020

Resting-state Co-activation Patterns as Accurate Predictors of Alzheimer's Disease in Aged Mice.

Alzheimers disease (AD), a neurodegenerative disorder marked by accumulation of extracellular amyloid-beta (A{beta}) plaques leads to progressive loss of memory and cognitive function. Resting state fMRI (RS-fMRI) studies have provided links between these two observations in terms of disruption of default mode and task positive resting state networks (RSNs). Important insights underlying these disruptions were recently obtained by investigating dynamic fluctuations in RS-fMRI signals in old TG2576 mice (mouse model of amyloidosis) using a set of quasi-periodic patterns (QPP). QPPs represent repeating spatiotemporal patterns of neural activity of predefined temporal length. In this article, we used an alternative methodology of co-activation patterns (CAPs) that represent instantaneous and transient brain configurations that are likely contributors to the emergence of commonly observed resting state networks (RSNs) and QPPs. We followed a recently published approach for obtaining CAPs that divided all time frames, instead of those corresponding to supra-threshold activations of a seed region as done traditionally, to extract CAPs from RS-fMRI recordings in 10 TG2576 female mice and 8 wild type littermates at 18 months of age. Subsequently we matched the CAPs from the two groups using the Hungarian method and compared the temporal (duration, occurrence rate) and the spatial (lateralization of significantly activated voxels) properties of matched CAPs. We found robust differences in the spatial components of matched CAPs. Finally, we used supervised learning to train a classifier using either the temporal or the spatial component of CAPs to distinguish the transgenic mice from the WT. We found that while duration and occurrence rates of all CAPs performed the classification with significantly higher accuracy than the chance-level, blood oxygen level dependent (BOLD) signals of significantly activated voxels from individual CAPs turned out to be a significantly better predictive feature demonstrating a near perfect classification accuracy. Our results demonstrate resting-state co-activation patterns are a promising candidate for a diagnostic, and potentially, prognostic biomarker of Alzheimers disease.

neuroscience↗

bioRxiv2019

Increased soluble amyloid-beta causes early aberrant brain network hypersynchronisation in a mature-onset mouse model of amyloidosis

BackgroundAlzheimers disease (AD) is the most common form of dementia in the elderly population. Currently, no effective cure is available for AD. According to the amyloid hypothesis, the accumulation and deposition of the amyloid-beta (A{beta}) peptides plays a key role in AD pathology. Soluble A{beta} (sA{beta}) oligomers were shown to be synaptotoxic and involved in pathological hypersynchronisation of brain resting-state networks in different transgenic developmental-onset mouse models of amyloidosis. However, the impact of protein overexpression during brain postnatal development may cause additional phenotypes unrelated to AD. To address this concern, we investigated sA{beta} effects on functional resting-state networks in transgenic mature-onset amyloidosis Tet-Off APP (TG) mice.\n\nMethodsTG mice and control littermates were raised on doxycycline (DOX) diet from 3d up to 3m of age to suppress transgenic A{beta} production. Thereafter, longitudinal resting-state functional MRI was performed on a 9.4T MR-system starting from week 0 (3m old mice) up to 28w post DOX treatment. Ex vivo immunohistochemistry and ELISA analysis (additional mice cohort) was performed to address the development of amyloid pathology.\n\nResultsFunctional Connectivity (FC) analysis demonstrated early abnormal hypersynchronisation in the TG mice compared to the controls at 8w post DOX treatment. This effect was observed particularly across regions of the default mode-like network, known to be affected in AD. Ex vivo analyses performed at this time point confirmed a 20-fold increase in total sA{beta} levels and the absence of A{beta} plaques in the TG mice compared to the controls. On the contrary at week 28, TG mice showed an overall hypoconnectivity, coinciding with a widespread deposition of A{beta} plaques in the brain.\n\nConclusionsBy preventing developmental influence of APP and/or sA{beta} during brain postnatal development, we demonstrated FC abnormalities driven by sA{beta} synaptotoxicity on resting state neuronal networks in mature-induced TG mice. Thus, the Tet-Off APP mouse model could be a powerful tool while used as a mature-onset model to shed light into amyloidosis mechanisms in AD. Therefore, this inducible APP expression model used in combination with early non-invasive in vivo rsfMRI readout for sA{beta} synaptotoxicity sets the stage for future A{beta} targeting preventative treatment studies.

neuroscience↗

bioRxiv2019

Chemogenetic silencing of neurons in the mouse anterior cingulate area modulates neuronal activity and functional connectivity

The anterior cingulate area (ACA) is an integral part of the prefrontal cortex in mice and has been implicated in several cognitive functions. Previous anatomical and functional imaging studies demonstrated that the ACA is highly interconnected with numerous brain regions acting as a hub region in functional networks. However, the importance of the ACA in regulating functional network activity and connectivity remains to be elucidated. Recently developed neuromodulatory techniques, such as Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) allow for precise control of neuronal activity. In this study, we used an inhibitory kappa-opioid receptor DREADDs (KORD) to temporally inhibit neuronal firing in the right ACA of mice and assessed functional network activity and connectivity using non-invasive functional MRI. We demonstrated that KORD-induced inhibition of the right ACA induced blood oxygenation-level dependent (BOLD) signal decreases and increases in connected brain regions throughout of hemispheres. Furthermore, these modulations in neuronal activity were associated with decreased intra- and interhemispheric functional connectivity. These results demonstrate that the combination of the DREADD technology and non-invasive functional imaging methods is a valuable tool for unraveling the underlying mechanisms of network function and dysfunction.

neuroscience↗

bioRxiv2019

Resting brain fluctuations are intrinsically coupled to visual response dynamics

How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional (f)MRI to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) govern mouse resting brain dynamics. QPPs captured the temporal alignment of global brain fluctuations, anti-correlation of the Default Mode (DMN)- and Task Positive (TPN)-like networks, and activity in neuromodulatory nuclei of the reticular formation. While visual stimulation could trigger a transient spatiotemporal pattern highly similar to intrinsic QPPs, global signal fluctuations and QPPs during rest periods could explain variance in the following visual responses. QPPs and the global signal thus appeared to capture a common arousal-related brain-state fluctuation, orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.

neuroscience↗

bioRxiv2019

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories world-wide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a murine default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

neuroscience↗

bioRxiv2018

Bottom-up sensory processing can decrease activity and functional connectivity in the default mode like network in rats.

The default mode network is a large-scale brain network that is active during rest and internally focused states and deactivates as well as desynchronizes during externally oriented (top-down) attention demanding cognitive tasks. However, it is not sufficiently understood if unpredicted salient stimuli, able to trigger bottom-up attentional processes, could also result in similar reduction of activity and functional connectivity in the DMN. In this study, we investigated whether bottom-up sensory processing could influence the default mode like network (DMLN) in rats. DMLN activity was examined using block-design visual functional magnetic resonance imaging (fMRI) while its synchronization was investigated by comparing functional connectivity during a resting versus a continuously stimulated brain state by unpredicted light flashes. We demonstrated that activity in DMLN regions was decreased during visual stimulus blocks and increased during blanks. Furthermore, decreased inter-network functional connectivity between the DMLN and visual networks as well as decreased intra-network functional connectivity within the DMLN was observed during the continuous visual stimulation. These results suggest that triggering of bottom-up attention mechanisms in anesthetized rats can lead to a cascade similar to top-down orienting of attention in humans and is able to deactivate and desynchronize the DMLN.

neuroscience↗

bioRxiv2018

Predict future learning accuracy by the structural properties of the brain, an in vivo longitudinal MRI study in songbirds

Human speech and bird song are acoustically complex communication signals that are learned by imitation during a sensitive period early in life. Although the neural networks indispensable for song learning are well established, it remains unclear which neural circuitries differentiate good from bad song copiers. By combining in vivo structural Magnetic Resonance Imaging with song analyses in juvenile male zebra finches during song learning and beyond, we discovered that song imitation accuracy correlates with the structural architecture of four distinct brain areas, none of which pertain to the song control system. Furthermore, the structural properties of a secondary auditory area in the left hemisphere, are capable to predict future song copying accuracy, already at the earliest stages of learning, before initiating vocal practicing. These findings appoint novel brain regions important for song learning outcome and inform that ultimate performance in part depends on factors experienced before vocal practicing.

neuroscience↗